Interative stripewise trellis-based symbol detection method and device for multi-dimensional recording systems

ABSTRACT

When processing a two dimensional data area it is known to be advantageous to divide the two dimensional are into stripes and process each stripe using a stripe-wise detector. The stripe being processed shifts row per row downwards. Each stripe has as its output the bit-decisions of the top bit-row of the stripe which is the most reliable. That output bit-row is also used as side-information for the bit detection of the next stripe which is the stripe which is shifted one bit-row downwards. The bit-row just across the bottom of the stripe on the other hand still needs to be determined in the current iteration, so only the initialisation bit-values can be used in the first iteration of the stripe-wise bit-detector. In order to prevent the propagation of errors towards the top bit row of the stripe the relative weight for the bottom branch bit in the figure-of-merit is reduced from the full 100% to a lower fraction.

FIELD OF THE INVENTION

The invention relates to a trellis-based symbol detection method fordetecting symbols of a channel data block recorded on a record carrier.The invention applies to digital recording systems, such as magneticrecording and optical recording systems. It is particularly advantageousfor two-dimensional optical recording, which is one of the potentialtechnologies for the next generations of optical recording.

BACKGROUND ART

Current state-of-the-art optical disc systems are based onone-dimensional (ID) Optical Recording. A single laser beam is directedat a single track of information, which forms a continuous spiral on thedisc, spiraling outwards to the outer edge of the disc. The singlespiral contains a single (or one dimensional, ID) track of bits. Thesingle track consists of sequences of very small pit-marks or pits andthe spaces between them, which are called land-marks or lands. The laserlight is diffracted at the pit structures of the track. The reflectedlight is detected on a photo-detector Integrated Circuit (IC), and asingle high-frequency signal is generated, which is used as the waveformfrom which bit-decisions are derived. A new route for the 4th generationof optical recording technology that will succeed “Blue Ray Disc” alsocalled “DVR” already succeeding DVD (Digital Video Disc) technology isbased on two-dimensional (2D) binary optical recording. 2D recordingmeans that e.g. 10 tracks are recorded in parallel on the disc withoutguard space in between. Then, the 10 tracks together form one bigspiral. The format of a disc for 2D optical recording (called in short a“2D disc”) is based on that broad spiral, in which the information isrecorded in the form of 2D features. The information is written as ahoneycomb structure and is encoded with a 2D channel code, whichfacilitates bitdetection. The disc shall be read out with an array ofe.g. 10 (or more) optical spots, which are sampled in time, in order toobtain a two dimensional array of samples in the player. Parallel readout is realized using a single laser beam, which passes through agrating, which produces the array of laser spots. The array of spotsscans the full width of the broad spiral. The light from each laser spotis reflected by the 2D pattern on the disc, and is detected on aphoto-detector IC, which generates a number of high frequency signalwaveforms. The set of signal waveforms is used as the input of the 2Dsignal processing. The motivation behind 2D recording is that much lessdisc space is wasted as guard space, so that the recording capacity ofthe disc can be increased. Although 2D recording is first studied foroptical recording, similarly, magnetic recording can also be madetwo-dimensional. One of the new aspects of such recording techniques isthat they require two dimensional signal processing. In particular, oneoptical spot must be considered as a device which takes a plane of“pits”/“lands” (or “marks” and “non-marks”) as input and produces acorresponding output. The optical spot transfer function has thecharacteristics of a 2D low pass filter, whose shape can be approximatedby a cone. Apart from its linear transfer characteristics, the 2Doptical channel also has non-linear contributions. The radius of thecone corresponds to the cutoff frequency, determined by the numericalaperture of the lens, and the wavelength of the light. This filteringcharacteristic causes 2D Inter Symbol Interference (ISI) in the player.It is the task of a bit-detector to annihilate (most of) this ISI (whichcan be both linear and nonlinear). An optimal way to implement abit-detector is to use a Viterbi algorithm. A Viterbi bit detector doesnot amplify the noise. If soft decision output, i.e. reliabilityinformation about the bits, is required, a dual-Viterbi i.e.(Max-)(Log-)MAP, or MAP, or SOVA (Soft Output Viterbi) algorithm can beused. One of the difficulties of designing a bit-detector for the 2Dcase, is that a straightforward Viterbi bit-detector would need as its“state”, one or more columns of “old” track bits because of the memoryof the ISI. If e.g. 10 tracks are recorded in parallel in the 2D broadspiral, and e.g. two old bits per track is needed for a properdescription of the state because of the tangential extent(along-the-tracks) of the 2D impulse response, this results in a stateof 2×10=20 bits. Thus, the number of states in the Viterbi (or MAP,(Max-)(Log-)MAP, MAP, SOVA, etc.) algorithm becomes 2²⁰, which iscompletely impractical. This requires a different approach, which may beslightly sub optimal, but has a significantly reduced complexity. Byproviding a method of stripe wise bit detection where the stripe wisedetector uses side information from adjacent tracks the bit detection ofa broad spiral can be segmented, reducing the complexity of the overalldetection method. The use of side information however can introducederrors into the bit detection.

SUMMARY OF THE INVENTION

It is an object of the invention to provide a symbol detection methodthat does not degrade in performance due to unreliable side information.

To achieve this objective the bit detection method is characterized inthat a weighing of a contribution of the side information is assignedbased on a reliability of the side information

When, due to the nature of the source of the side information, the sideinformation is not reliable the contribution to the bit detection ofthis side information is reduced by applying a weighing factor inaccordance with the reliability of the side information. Thecontribution of unreliable side information receives a lower weighingfactor then the contribution of reliable side information.

An embodiment of the symbol detection method is characterized in thatthe contribution is a contribution to an objective function of thesearch based algorithm.

An objective function of a search based algorithm is typicallyminimizing the error between the transmitted or recorded data and thedetected data by searching among all candidate possibilities the mostlikely candidate. The contribution can be a contribution to a branchmetric.

An embodiment of the symbol detection method is characterized in thatthe search based algorithm comprises the use of internal contributionsand that the use of the internal contributions comprises assigning anindividual weighing of the internal contributions.

In addition to weighing the contribution of the side information fromoutside the stripe the contributions from within the stripe can also beweighed to reduce contribution from unreliable parts of the stripe.

For instance the detection of bits in a row directly adjacent to a yetto be processed stripe is unreliable because all bits around a bit to bedetected contribute to the detection of that bit but only the bitsinside the stripe are contributing to the detection with their mostlikely values while the value of the bits outside the stripe but stillcontributing to the detection of that bit are less reliable and in afirst iteration even unknown.

The weighing of the contribution of that bit, although inside thestripe, must be reduced in order to reduce the contribution from theunreliable bits just outside the stripe. If the bits outside the stripthat contribute to the detection are not yet known, they can be assumedto all have the value 0, 1 or have a random value in order to have avalue for the bit detection, even if that value is incorrect.

The bit being detected is thus less reliable and because the bit beingdetected is also used in the detection of its neighbors, those neighborsalso receive contributions that are less reliable than desirable.

The weighing of the contribution of the bit to the detection of otherbits in the stripe must thus also be reduced resulting in potentiallydifferent weighing of the contributions from inside the stripe.

An embodiment of the symbol detection method is characterized in thatthe search based algorithm is a Viterbi algorithm, a sequential decodingalgorithm such as a stack algorithm or a Fano algorithm, or asoft-decision output algorithm such as a (Max)(Log)MAP algorithm, or areduced complexity maximum likelihood detection algorithm.

The listed search based algorithms all can be used to perform bitdetection, allow the introduction of contribution of side informationand allow the weighing of contributions. They are there fore suitablealgorithms that can be used with the bit detection method according tothe invention.

An embodiment of the symbol detection method is characterized in thatthe side information is an estimated channel input symbol.

Hard decision bit detection methods produce side information in the formof an estimated channel input symbol. The contribution of the estimatedchannel input symbol is used during bit detection.

An embodiment of the symbol detection method is characterized in thatthe side information is likelihood information about a channel inputsymbol Soft decision bit detection algorithms produce side informationin the form of likelihood information about a channel input symbol. Thelikelihood information of the estimated input symbol is used during bitdetection.

An embodiment of the symbol detection method is characterized in that afurther side information, derived from the row adjacent to the firststripe, is being used in the estimation of said symbol values.

Not only side information derived from channel input symbols can be usedbut also other side information derived from the adjacent stripe can beused. All side information derived from the adjacent stripe contributeto a more reliable bit detection.

An embodiment of the symbol detection method is characterized in thatthe further side information comprises channel output values.

Not only side information derived from channel input symbols can be usedbut also other side information derived from the channel output valuesof the adjacent stripe can be used. This additional side informationwhen used in tandem with the side information derived from the estimatedinput symbols contributes to a more reliable bit detection.

An embodiment of the symbol detection method is characterized in thatthe channel output values are filtered channel output values.

Filtered output values are often readily available and can be used toderive side information from.

An embodiment of the symbol detection method is characterized in that aweighing of the contribution of the side information is highest for sideinformation derived from a symbol detection with a highest reliability.

There can be multiple adjacent or overlapping stripes for a stripe to beprocessed. Each adjacent stripe then provides side information. In orderto improve the bit detection of the stripe to be processed eachcontribution from the side information of the adjacent stripes isweighed and more reliable contribution are given a higher weight thanless reliable contributions. This way the less reliable contributionscontribute less to the bit detection resulting in a more reliable bitdetection.

An embodiment of the symbol detection method is characterized in thatthe symbol detection with the highest reliability is a symbol detectionfrom a previous iteration. With every iteration the reliability of theside information derived from the bit detection of that iterationincreases because the reliability of the overall bit detection increaseswith every iteration.

Thus the weightings can be increased from one iteration to the next toreflect this increased reliability of the side information.

An embodiment of the symbol detection method is characterized in thatthe weighing is based on a distance between a position of a symbol valueto be detected and a position of a side information symbol position.

When side information is located further away from the position of thesymbol value to be detected the contribution of that side information isless than when the side information is located close to the symbol valueto be detected. The weighing reflects this reduced contribution. Thisassures that side information from further away from the symbol value tobe detected contributes less to the symbol detection.

An embodiment of the symbol detection method is characterized in thatthe distance is a distance to a most reliable side information positionand that the weighing is a highest weighing.

The side information derived from the closest distance has the largestcontribution to the symbol detection.

The weighing reflects this contribution by assigning the highest weightto the contribution of this side information.

An embodiment of the symbol detection method is characterized in thatthe weighing of the contribution of the side information is differentfor the second detector compared to the first detector

When the stripe is processed by multiple bit detectors in parallel theweighing of contributions can differ from one detector to anotherdetector, for instance because the reliability of the symbol detectionfrom which the side information is derived varies from stripe to stripeacross the broad spiral which the stripes together form.

An embodiment of the symbol detection method is characterized in thatthe weighing of the contribution of the side information is differentfor a second iteration compared to a first iteration.

When the stripe is processed in multiple iterations the weighing can bevaried to reflect the increase or decrease in reliability of the sideinformation from one iteration to the next iteration.

An embodiment of the symbol detection method is characterized in thatthe weighing of the contribution of the side information is higher forthe second iteration compared to the first iteration.

In general the reliability of the symbol detection and thus of the sideinformation increases from one iteration to the next iteration. Theweighing can be adjusted to reflect this increase in reliability fromone iteration to the next iteration.

An embodiment of the symbol detection method is characterized in thatthe side information is obtained from a row comprising data which ishighly protected using redundant coding.

When a row comprising data which is highly protected is comprised in thebroad spiral or delimits the broad spiral the side information derivedfrom this data is also more reliable than side information derived fromthe regular stripes. A higher weighing must therefore be assigned to theside information derived from data which is highly protected compared toside information derived from other data.

An embodiment of the symbol detection method is characterized in thatthe side information is obtained from a row comprising predefined data.

Predefined data is inherently reliable in detection because errors canbe easily corrected.

As a consequence side information derived from predefined data is alsoreliable. The weighing of side information derived from predefined datacan thus be higher than the weighing of side information derived fromother data.

An embodiment of the symbol detection method is characterized in thatthe row comprising data which is highly protected using redundant codingis a guard band.

A guard band often comprises predefined data or is highly protected inorder to assure correct detection of the guard band fro purposes oftracking etc. The guard band can thus be put to dual use by derivingside information from the data in the guard band and providing this sideinformation to the symbol detector of the stripe adjacent to the guardband to improve the reliability of the detection.

An embodiment of the symbol detection method is characterized in thatthe row comprising data which is highly protected using redundant codingis located centrally between the rows forming the set of symbol rows.

Typically a row comprising highly protected data is located such that itdelimits the data area. It is however also possible to locate such a rowin the middle of the data area. Such a highly protected row can belocated in the data area at a position where the stripe wise detectionis inherently less reliable, for instance near the center of the dataarea. In the case of a broad spiral the row would be located near themiddle of the broad spiral. Since the reliability of the row comprisinghighly protected propagates to the adjacent stripes which use, directlyor indirectly, use side information from the row comprising highlyprotected data, such a row can be appropriately positioned to enhancethe detection where needed.

An embodiment of the symbol detection method is characterized in thatthe N-Dimensional channel tube is delimited by multiple guard bands.

By using multiple guard bands the methods outlined in the previousembodiments can be used to start multiple bit detectors in parallel.Near each guard band a bit detector starts, using the side informationderived from that guard band, a cascade of bit detectors where each bitdetector in the cascade closely trails the previous detector in thecascade. When using the 2 dimensional broad spiral as an example therewould be for instance 2 guard bands, a first guards band delimiting thebroad spiral at the top and a second guard band delimiting the broadspiral at the bottom. A first cascade of bit detectors starts at thefirst guard band and propagating the increased reliability down in thecascade towards the second guard band. A second cascade of bit detectorsstarts at the second guard band and propagating the increasedreliability up in the cascade towards the first guard band.

The two cascades of bit detectors would meet somewhere on the broadspiral, for instance at the middle of the broad spiral, each havingprocessed the upper portion of stripes of the broad spiral, respectivelythe lower portion of stripes of the broad spiral.

In a graphic sense the cascades of bit detectors form a V shapeconstellation of bit detectors where the open end of the V shape pointsin the direction of processing of the broad spiral.

Where the two cascades meet one can choose to process a final stripeusing either the side information from the cascade having processed thelower portion of stripes, the side information from the cascade havingprocessed the upper portion of stripes, or both side informations.

In addition it is possible to have a bit detector from both cascadesprocess the final stripe.

By working both the upper and lower portion of the broad spiral inparallel the processing time is greatly reduced.

An embodiment of the symbol detection method is characterized in thatside information is derived from each guard band of the multiple guardbands.

A symbol detector using one of the embodiments of the method accordingto the invention benefits from a decrease in time required to processthe broad spiral or other N-dimensional data.

A playback device using a symbol detector according to the inventionbenefits from a decrease in time required to process the broad spiral orother N-dimensional data.

A computer program implementing a symbol detector using the methods ofthe present invention would benefit from a decrease in time required toprocess the broad spiral of other N-dimensional data.

It should be noted that the channel output is not necessarily sampled ona lattice, nor is it necessary that the channel output are sampled on asimilar lattice as the lattice of channel inputs (recorded marks). E.g.the channel outputs may be sampled according to a lattice hat is shiftedwith respect to the lattice of channel inputs (recorded marks), e.g.sampling may take place above edges of the cells of a hexagonal lattice.Also, (signal) dependent oversampling may be applied with higher spatialsampling densities in certain directions as compared to otherdirections, where these directions need to be aligned with respect tothe lattice of signal inputs (recorded marks).

1. detected symbols are channel symbols.

2. detected symbols are a linear function of the channel symbols.

3. detected symbols are a linear function of the channel symbols andestimates from preceding iterations of those channel symbols.

4. detected symbols are a linear function of the channel symbols andestimates from preceding iterations of a linear function of the channelsymbols.

The invention will now be described based on figures.

FIG. 1 shows a record carrier comprising a broad spiral.

FIG. 2 shows the contributions of leaked away signal energy.

FIG. 3 shows the states and branches for a viterbi detector in a threerow stripe.

FIG. 4 shows multiple detectors processing a broad spiral.

FIG. 5 shows the reduction of weights in a stripe wise bit detector

FIG. 6 shows the extension of the computation of branch metrics withsamples of the signal waveform at bits in the bit row above the stripe.

FIG. 7 shows a stripe wise bit detection along a broad spiral where thestripe is oriented in a different direction.

FIG. 1 shows a record carrier comprising a broad spiral.

The invention concerns with an extension of the concept of branchmetrics to be used for the processing along a Viterbi-trellis of astripe, involving (i) signal waveform samples of bits outside of thestripe, thus not belonging to the states of the Viterbi processor forthe stripe considered and (ii) the introduction of reduced weightssmaller than the maximum weight (set equal to 1) for the separate termsin the branch metric that are related to the different bit-rows withinthe stripe, and (iii) the introduction of cluster-driven weights due tosignal-dependent noise characteristics.

The context of this invention is the design of a bit-detection algorithmfor information written in a 2D way on a disc 1 or a card. For instance,for a disc 1, a broad spiral 2 consists of a number of bit-rows 3 thatare perfectly aligned one with respect to the other in the radialdirection, that is, in the direction orthogonal to the spiral 2direction. The bits 4 are stacked on a regular quasi close-packedtwo-dimensional lattice. Possible candidates for a 2D lattice are: thehexagonal lattice, the square lattice, and the staggered rectangularlattice. This description is based on the hexagonal lattice because itenables the highest recording density.

For ambitious recording densities the traditional “eye” is closed. Insuch a regime, the application of a straightforward threshold detectionwill lead to an unacceptably high bit error rate (10⁻² to 10⁻¹,dependent on the storage density), prior to ECC decoding. Typically, thesymbol or byte error-rate (BER) for random errors in the case of abyte-oriented ECC (like the picket-ECC as used in the Blu-Ray DiscFormat, BD) must be not larger than typically 2 10⁻³; for an uncodedchannel bit stream, this corresponds to an upper bound on the allowablechannel-bit error rate (bER) of 2.5 10⁻⁴.

On the other hand, full-fledged PRML type of bit-detectors would requirea trellis which is designed for the complete width of the broad spiral2, with the drawback of an enormous state-complexity. For instance, ifthe horizontal span of the tangential impulse response along thedirection of the broad spiral 2 is denoted by M, and if the broad spiralconsists of N_(row) bit-rows, then the number of states for thefull-fledged “all-row” Viterbi bit-detector becomes 2ˆ((M-1) N_(row))(where ˆ denotes exponentiation). Each of these states has also 2ˆ(MN_(row)) predecessor states, thus in total the number of branches ortransitions between states equals 2ˆ(M N_(row)). The latter number(number of branches in the Viterbi trellis) is a good measure for thehardware complexity of a 2D bit-detector.

Ways to largely circumvent this exponentially growing state-complexityare the breakdown of the broad spiral 2 into multiple stripes. Thestate-complexity can be reduced by a stripe-based PRML-detector, anditerating from one stripe towards the next. Stripes are defined as a setof contiguous “horizontal” bit-rows in the broad spiral. Such abit-detector is shortly called a stripe-wise detector. The recursionbetween overlapping stripes, the large number of states, i.e. 16 for astripe of 2 rows, and 64 states for a stripe of 3 rows, and theconsiderable number of branches, i.e. 4 for a stripe of 2 rows, and 8for s stripe of 3 rows, and the recursive character of each individualPRML detector make that the hardware complexity of such a detector canstill be quite considerable.

FIG. 2 shows the contributions of leaked away signal energy.

The signal-levels for 2D recording on hexagonal lattices are identifiedby a plot of amplitude values for the complete set of all hexagonalclusters possible. An hexagonal cluster 20 consists of a central bit 21at the central lattice site, and of 6 nearest neighbour bits 22 a, 22 b,22 c, 22 d, 22 e, 22 f at the neighbouring lattice sites. The channelimpulse response is assumed to be isotropic, that is, the channelimpulse response is assumed to be circularly symmetric. This impliesthat, in order to characterize a 7-bit hexagonal cluster 20, it onlymatters to identify the central bit 21, and the number of “1”-bits (or“0”-bits) among the nearest-neighbour bits 22 a, 22 b, 22 c, 22 d, 22 e,22 f (0, 1, . . . , 6 out of the 6 neighbours can b a “1”-bit). A“0”-bit is a land-bit in this description.

Note that the isotropic assumption is purely for the purpose of concisepresentation. In a practical drive with a tilted disc, the 2D impulseresponse can have asymmetry. There are two solutions for the latterissue: (i) to apply a 2D equalizing filter restoring a rotationallysymmetric impulse response, and (ii) application of a larger set ofreference levels to be used in the branch metric computation, whereineach rotational variant of a given cluster has its own reference level;for this general case, for a 7-bit cluster, consisting of a central bit21 and its six neighbours 22 a, 22 b, 22 c, 22 d, 22 e, 22 f, we willhave 2ˆ7=128 reference levels, instead of the 14 reference levels incase of the isotropic assumption of above.

The channel bits that are written on the disc are of the land type (bit“0”) or of the pit-type (bit “1”). With each bit a physical hexagonalbit-cell 21, 22 a, 22 b, 22 c, 22 d, 22 e, 22 f is associated, centeredaround the lattice position of the bit on the 2D hexagonal lattice. Thebit-cell for a land-bit is a uniformly flat area at land-level; apit-bit is realized via mastering of a (circular) pit-hole centered inthe hexagonal bit-cell. The size of the pit-hole is comparable with orsmaller than half the size of the bit-cell. This requirement eliminatesthe “signal folding” issue, which would arise for a pit-hole that coversthe full area of the hexagonal bit-cell 21, 22 a, 22 b, 22 c, 22 d, 22e, 22 f : in such case, both for a cluster of all zeroes (all-land) aswell as for a cluster of all ones (all-pit), a perfect mirror results,with identical signal levels for both cases. This ambiguity in signallevels must be avoided since it hampers reliable bit-detection.

For high-density 2D optical storage, the 2D impulse response of the(linearized) channel can be approximated to a reasonable level ofaccuracy by a central tap with tap-value co equal to 2, and with 6nearest-neighbour taps with tap-value c₁ equal to 1. The total energy ofthis 7-tap response equals 10, with an energy of 6 along the tangentialdirection (central tap and two neighbour taps), and an energy of 2 alongeach of the neighbouring bit-rows (each with two neighbour taps).

From these energy considerations, one of the main advantages of 2Dmodulation can be argued to be the aspect of “joint 2D bit-detection”,where all the energy associated with each single bit is used forbit-detection. This in contrast to 1D detection with standard cross-talkcancellation, where only the energy “along-track” is being used, thusyielding a 40% loss of energy per bit.

A similar argumentation holds when we consider bit detection at theedges of a 2D stripe (for which we want to output the top bit-row). Ofthe order of 20% of the signal-energy of the bits in the top-row hasleaked away in the samples of the signal waveform of the two samples inthe bit-row just above the stripe: these two samples are located atnearest neighbour sites of the bit in the top row of the current stripe.The other 20% leaking away from the top bit-row is leaking away in thebit-row below the top bit-row in the stripe: this energy is used becausethe stripe of at least two bit-rows wide comprises also the bit-rowbelow the top bit-row of the stripe. Consequently, not using the leakedaway information, that has been leaking away in the “upward” direction(when the top bit-row is the output of the considered stripe), wouldlead to a loss in bit-detection performance at the top row of thestripe.

The solution to the above drawback is to include the HF-samples in thebit-row above the stripe in the computation of the figure-of-merit. Notethat only the samples of the signal waveform of that row do matter here,and that the bits in that row are not varied since they do not belong tothe set of bits that are varied along the trellis and states of theViterbi-detector for the stripe considered. Denoting the row-index ofthe bit-row above the stripe by l-l, the branch metric is denoted by(with the running index j now starting from “−1”):$\beta_{mn} = {\sum\limits_{j = {- 1}}^{2}{w_{j}{{{HF}_{k,{l + j}} - {{RL}\left( {{\sum_{m}{->\sum_{n}}},j,l} \right)}}}^{2}}}$This extension of the computation of the branch metrics with inclusionof the row of signal samples in the bit-row above the stripe isschematically drawn in FIG. 6. Note that in the computation of thereference levels, all the required bits within the stripe are set by thetwo states that constitute a given branch, and all the required bitsoutside the stripe are determined by the previous stripe in the currentiteration of the stripe-wise bit-detector, or by the previous iterationof the stripe-wise bit-detector.

For the sake of completeness, note that the above description applies toa top-to-bottom processing of the stripes, wherein the output of eachstripe is its top bit-row, and the extra bit-row that is accounted forin the branch metrics, is the row just above the stripe, with indexj=−1. However, for the opposite processing order, from bottom-to-top,the output of each stripe is its bottom bit-row, and the extra bit-rowthat is accounted for in the branch metrics, is the row just below thestripe, with index j=3 (for a 3-row stripe).

FIG. 3 shows the states and branches for a viterbi detector in a threerow tripe.

First the basic structure of the trellis as shown in FIG. 3 isexplained, addressing the practical case of a 3-row stripe 30. Thetangential span of the 2D impulse response is assumed to be 3 bits wide,a situation that meets the practical conditions for the high-densityrecording on a hexagonal grid. A state 31 a, 31 b is specified by twocolumns extending over the full radial width of 3 rows 33 a, 33 b, 33 cof the stripe 30. There are thus in this example exactly 2ˆ6=64 states.The pace of the Viterbi bit-detector goes with the frequency of emissionof a 3-bit column 34. Emission of a 3-bit column 34 corresponds with astate transition from a so-called departure state Σ_(m) 31 a to aso-called arrival state Σ_(m) 31 b. For each arrival state 31 b, thereare exactly 8 possible departure states 31 a and thus 8 possibletransitions. A transition between two states 31 a, 31 b is called abranch in the standard Viterbi/PRML terminology. For each transition,there are thus two states and thus a total of 9 bits that are completelyspecified by these two states. For each branch, there are a set ofreference values which yield the ideal values of the signal waveform atthe branch bits these ideal values would apply if the actual 2Dbit-stream along the stripe 30 would lead to the considered transitionin the noise free case. With each transition a branch metric can beassociated which gives a kind of “goodness-of-fit” or “figure-of-merit”for the considered branch or transition based on the differences thatoccur between the observed “noisy” signal waveform samples, denoted byHF, and the corresponding reference levels which are denoted by RL. Itshould be noted that the noise on the observed samples of the waveformcan be due to electronic noise, laser noise, media noise, shot noise,residual ISI beyond the considered span of the 2D impulse response etc.It is common practise to consider as the branch bits, at which thesedifferences for the figure-of-merit are to be measured, the bits thatare common to both states 31 a, 31 b that constitute the branch: in FIG.3, this would be the 3 bits of the column at the intersection of the twostates 31 a, 31 b. Thus, if k denotes the tangential index at theposition of the intersection column, and l denotes the top bit-row 33 aof the stripe 30, the branch metric β_(mn) between the state Σ_(m) 31 aand the state Σ_(n) 31 b is given by:$\beta_{mn} = {\sum\limits_{j = 0}^{2}{{{HF}_{k,{l + j}} - {{RL}\left( {{\sum_{m}{->\sum_{n}}},j,l} \right)}}}^{2}}$

The above formula is based on the assumption of a quadratic errormeasure for the figure-of-merit (L₂-norm), which is optimum for theassumption of additive white aussian noise (AWON). It is also possibleto use or error measures, like the absolute value of the difference(known as L₁-norm). For the determination of a reference level for a bitat a given location k, l+j on the 2D lattice, the values of the sixsurrounding bits 22 a, 22 b, 22 c, 22 d, 22 e, 22 f around the locationk, l+j are needed together with the value of the central bit 21: these 7bits 21, 22 a, 22 b, 22 c, 22 d, 22 e, 22 f uniquely specify thereference level to be used for the considered state transition or branchat the considered bit-location 21.

FIG. 4 shows multiple detectors processing a broad spiral.

The standard way of operation of the stripe-wise bit-detector will nowbe described. A stripe 41 a, 41 b, 41 c consists of a limited number ofbit-rows 42 a, 42 b. For FIG. 4, the practical case of a stripecomprising two bit-rows in a stripe. Note that in FIG. 4, a bit-row isbounded by two horizontal lines at its edges. The number of stripes isequal to the number of bit-rows in the case of two bit rows per stripe.A set of Viterbi bit-detectors V00, V01, V02 is devised, one for eachstripe. The bits outside of a given stripe that are needed for thecomputation of the branch metrics, are taken from the output of aneighbouring stripe, or are assumed to be unknown. In a first iterationthe unknown bits may be set to zero. The first top-stripe 43, containingas its top row, the bit-row 44 a closest to the guard band is processedby bit detector V00 without any delay at its input; it uses the bits ofthe guard band as known bits. The output of the bit detector V00processing the first stripe are the bit-decisions in the first bit-row44 a. The second stripe 45 contains the second row 44 b and the thirdbit-row 44 c, and is processed by the second bit detector V01 with adelay that matches the back-tracking depth of the Viterbi-detector ofthe first stripe 43, so that the detected bits from the output of thebit detector V00 processing the first stripe 43 can be used for thebranch metrics of the second stripe 45. This procedure is continued forall stripes in the broad spiral 2. The full procedure from top to bottomof the broad spiral 2 is considered to be one iteration of thestripe-wise detector. Subsequently, this procedure can be repeatedstarting again from the guard band 46 at the top: for the bits in thebit-row just below the bottom of a given stripe, the bit-decisions fromthe previous iteration can be used.

In a top-to-bottom processing of successive stripes, the last stripeprocessor V10 is assumed to output its top bit-row. Anotherimplementation is possible here: the bottom stripe bit detector V10could be omitted, and alter the 2-row stripe processor V09 to processthe three bottom bit rows 44 i, 44 j, 44 k, thus processing the twobottom rows 44 j, 44 k of the broad spiral 2 such that it outputs bothrows simultaneously.

FIG. 5 shows the reduction of weights in a stripe wise bit detector

In FIG. 4 it has been shown that a stripe being processed is shiftedfrom the top of the broad spiral in the downward direction towards thebottom of the spiral. The stripe being processed shifts row per rowdownwards. Each stripe has as its output the bit-decisions of the topbit-row of the stripe which is the most reliable. That output bit-row isalso used as side-information for the bit detection of the next stripewhich is the stripe which is shifted one bit-row downwards. The bit-rowjust across the bottom of the stripe on the other hand still needs to bedetermined in the current iteration, so only the initialisationbit-values can be used in the first iteration of the stripe-wisebit-detector, or in any subsequent iteration. The bit-decisionsresulting from the previous iteration of the stripe-wise bit-detectorcan be used for that bit row. Therefore, in FIG. 5 the bit-decisions ofthe three row stripe wise bit detector V02 in the upper bit-row 51 aremore reliable than the bit-decisions in the bottom bit-row 53. This isthe reason why the output of one stripe is its top bit-row. Also, forthe computation of the required reference levels in the bottom bit-row,we need as explained in FIG. 2, the six nearest neighbour bits of thebranch bit 54 in the bottom bit-row; two neighbour bits 55 a, 55 b ofthese nearest neighbour bits are located in the bit-row 56 just belowthe stripe considered, and only preliminary bit-decisions, for instancefrom the previous iteration, are available for these neighbour bits 55a, 55 b. Consequently, in case of bit-errors in these two neighbour bits55 a, 55 b in the bit-row 56 below the current stripe 50, these errorswill affect the selected branches in the surviving path along theViterbi trellis: actually, the bit-errors in these two neighbour bits 55a, 55 b may be compensated by selecting the wrong bits in the statesalong the stripe, so that the error measure at the bottom branch bit canbe kept low enough. Unfortunately, this balancing will propagate errorstowards the top bit-row 51 of the stripe 50, which should be prohibited.

In order to prevent the propagation of errors towards the top bit row 51of the stripe 50 the relative weight for the bottom branch bit in thefigure-of-merit is reduced from the full 100%, i.e. a weighting of 1, toa lower fraction. With w₁ denoting the weight of the branch bit in thei-th row of the stripe, the branch metric becomes:$\beta_{mn} = {\underset{j = 0}{\overset{2}{\sum w_{j}}}{{{HF}_{k,{l + j}} - {{RL}\left( {{\sum_{m}{->\sum_{n}}},j,l} \right)}}}^{2}}$

By choosing the weight of the bottom row 53 in the stripe 50 to be muchlower than 1, the negative influence of the unknown or only preliminaryknown bits 55 a, 55 b in the bit-row 56 just below the current stripe 50is largely reduced. The weights of the respective contributions of thesignal waveforms to the branch metrics can also be varied from oneiteration to the next because the bit-decisions at the surrounding bitsbecome gradually more and more reliable.

For the sake of completeness, note that the above description applies toa top-to-bottom processing of the stripes, wherein the output of eachstripe is its top bit-row, and the weight of the bottom bit-row isreduced. However, for the opposite processing order, from bottom-to-top,the output of each stripe is its bottom bit-row, and the weight of thetop bit-row is reduced.

Further more, when the processing of the stripe comprises sideinformation from both adjacent stripes, the weight of the top bit rowand the bottom bit-row are both reduced.

In detection theory, it is a well-known known fact that in an optimalViterbi detector, the branch metrics are (negative) log-likelihoods ofthe channel input bits given the observed channel output values. Thebranch metric formula$\beta_{mn} = {\sum\limits_{j = 0}^{2}{{{HF}_{k,{l + j}} - {{RL}\left( {{\sum_{m}{->\sum_{n}}},j,l} \right)}}}^{2}}$derives its validity from the assumption that the noise is Additive,Gaussian and White. The squares inside the sum above stem from thelogarithm of the Gaussian probability density function of the noiseg_(mn) which also contains a square,${- {\log\left( {\Pr\left\{ {g_{mn} = g} \right\}} \right)}} = {{\frac{1}{2}{\log\left( {2\pi\quad N} \right)}} + \frac{g^{2}}{2N}}$

The whiteness assumption of the noise implies that different noisecomponents are statistically independent, so that their probabilitydensity functions can be multiplied. Therefore, their log-likelihoodfunctions can be added, as in the β_(mn) formula.

The problem we want to consider here, is that e.g. for an opticalrecording the variance of the noise N may depend on the central inputbit of a given channel output HF_(k,l+j) and its cluster of nearestneighbour inputs. For example, in case laser noise is dominant, largerchannel outputs HF_(k,l+j) carry more (multiplicative) laser noise(which is usually referred to as ‘RIN’, “relative intensity noise”).This leads to the question what value of the noise N to use in thebranch metric formula for β_(mn)?

The solution to this problem is very simple. Based on a table of thecluster-dependent noise variances, we make a table for the noisevariance N(Σ_(m)→Σ_(n), j) as a function of the state transition(E_(m)→F_(n)) and the row index j, and we divide by the adjusted valueof N in the branch metric formula,$\beta_{mn} = {\underset{j = 0}{\overset{2}{\sum w_{j}}}\frac{{{{HF}_{k,{l + j}} - {{RL}\left( {{\sum_{m}{->\sum_{n}}},j,l} \right)}}}^{2}}{N\left( {{\sum_{m}{->\sum_{n}}},j,l} \right)}}$

When the noise is really dependent on the cluster and on the centralinput bit of a given channel output, taking account of this as in thebranch metric formula above makes the branch metrics more closely equalto the log-likelihood functions as stated in the introduction of thissubsection. This in general results in an improvement of the resultingbit error rate at the bit-detector output.

FIG. 6 shows the extension of the computation of branch metrics withsamples of the signal waveform at bits in the bit row above the stripe.

In FIG. 4 it has been shown that a stripe is shifted from the top of thebroad spiral in the downward direction towards the bottom of the spiral.The stripe wise processing shifts row per row downwards. Each stripewise detector has as its output the bit-decisions derived from the topbit-row of the stripe which is the most reliable. That output bit-row 66of the previous stripe is also used as side-information for the bitdetection of the next stripe 60 which is the stripe which is shifted onebit-row downwards. As shown in FIG. 6 the stripe 60 comprises three bitrows 61, 62, 63. In FIG. 5 it was explained that the weighting of thebottom bit row 63 is reduced to prevent errors caused by the higheruncertainty associated with the bits in the lower bit row 63 frompropagating upward.

The output bit-row 66 as produced by the bit detection of the previousstripe has a higher reliability and the bits 65 a, 65 b of this bit row66 can be used as side information for the processing of the next stripe60. Especially when the output bit row 66 as produced by the bitdetection of the previous stripe is derived from a guard band. The guardband has very well encoded information or even predefined data resultingin a 100% reliability of the side information used in the bit detectionof the next stripe 60.

In the particular case of a broad spiral with two guard bands with bitsthat are known to the detector, the bit-reliability of the two anchorbit-rows is 100%. Another example is the case of a 2D format with anextra bit-row in the middle of the spiral, that is encoded such that ithas a higher bit-reliability than the other rows; then, two V-shapedprogressions of stripes can be devised, one operating between the centerbit-row and the upper guard band, the other operating between the samecenter bit-row and the lower guard band. For instance, the centerbit-row may be channel encoded with a 1D runlength limited (RLL) channelcode that enables robust transmission over the channel: for instance, ad=1 RLL channel code removes some of the clusters (those with a “1”central bit and all six “0”'s as neighbour bits, and vice versa) in theoverlap area of the signal patterns, hereby increasing the robustness ofbit-detection on the one hand, but reducing the storage capacity forthat row on the other hand because of the constrained channel coding.

During back-tracking of a Viterbi-processor for a given stripe, it is anoption to output all bit-rows of the stripe so that a bit-array with themost recent bit-estimates are stored. The purpose of this measure is toachieve a more uniform architecture for the Viterbi-processors in thetop-halt bottom-half and central area of a V-shaped bit-detectionscheme.

Prior to any Viterbi bit-detection, it is advantageous to have somepreliminary bit-decisions albeit at a relatively poor bit-error rate(bER) performance. For instance, at one side of each stripe, bits thathave been determined from the previous stripe or are set to zero whenthe stripe is located directly next to the guard band; at the other sideof the stripe, bit-decisions are needed in order to be able to derivereference levels for the bits in the neighbouring bit stripe within thestripe: these bit-decisions can be derived from a previous iteration ofthe stripe-wise bit-detector, or from preliminary bit-decisions when thefirst iteration of the stripe-wise bit-detector is being executed. Thesepreliminary decisions can just be obtained by putting all bits to zero,which is not such a clever idea.

A better approach is to apply threshold detection based on thresholdlevels (or slicer levels) that depend on whether the row is neighbouringthe guard band (consisting of all zeroes) or not. In the case of abit-row neighbouring the guard band, some cluster-levels are forbidden.Consequently, the threshold level is shifted upwards. It is computed asthe level between the cluster-level for a central bit equal to 0 andthree 1 -bits as neighbour, and the cluster-level for a central bitequal to 1 and one 1-bit as neighbour. The expected bit-error rate ofthis simple threshold detection is then, for this case, equal to 2/32,which is about 6%. In the case of a bit-row that is not neighbouring theguard-band, the threshold level is computed as the level between thecluster-level for a central bit equal to 0 and four 1-bits as neighbour,and the cluster-level for a central bit equal to 1 and two 1-bits asneighbour. The expected bit-error rate of this simple thresholddetection is then, for this case, equal to 14/128, which is about 11%.Although these bERs are quite high, they are considerably better,especially at the bit-rows neighbouring the guard bands, than the 50%bER obtained through coin tossing. These preliminary bit-decisionsobtained prior to the execution of the stripe-wise bit-detector can alsobe used as input for the adaptive control loops of the digital receiver(e.g. for timing recovery, gain- and offset-control, adaptiveequalization etc.) Note that the above derivation of the proper slicerlevels depends on the actual 2D storage density chosen and the resultingoverlap of signal levels in the “Signal Patterns”.

In FIG. 7 a different diagonal orientation of the stripe on the 2Dhexagonal lattice is shown. For such diagonal orientations, the shiftingof the stripe 71 comprising the three bit rows 72 a, 72 b, 72 c takesplace along the direction of the broad spiral 70. This implies that theViterbi processing with state-termination at the guard bands 73, 74where the bits are known to be zero, or a predefined value or a variableerror protected value, has to be completed before the shifting over thedistance of one bit along the tangential direction of the broad spiral70 can take place. The latter aspect is a real disadvantage with respectto parallelization of the hardware implementation. Different executionsof the stripe-wise bit-detector, operating along different directions,can be cascaded one after the other. Also, more oblique orientationsthan the ones shown in FIG. 7 can be devised. The orientation shown inFigure is one of the possibilites oriented along the basic axes of the2D hexagonal lattice, with angles of exactly 60 degrees between them.

One iteration of the stripe-wise bit-detector may consist as describedabove out of a successive processing of stripes 43, 45 starting from theguard band 46 on top of the broad spiral towards the guard band 80 atthe bottom of the broad spiral resulting in a linear row of detectorsV00, V01, V02, V03, V04, V05, V06, V07, V08, V09, V10 diagonal acrossthe broad spiral as shown in FIG. 4. Alternatively, one can start withstripes 43, 81 from both guard bands 46, 80 and successively process anumber of stripes proceeding from both sides towards the middle of thebroad spiral. Successive detectors V00, V00 a, V01, V01 a, V02, V02 a,V03, V03 a, V04, V04 a of the stripes are arranged in a V-shape as canbe seen in FIG. 8 for the practical case of a 11-row broad spiral andstripes 43, 45 consisting of two bit-rows. The Viterbi-detectors V00,V00 a, V01, V01 a, V02, V02 a, V03, V03 a, V04 are cascaded one afterthe other with mutual delay to allow for back-tracking of the respectivedetectors, and the cascade starts from the top guard-band 46 towards thecenter of the broad spiral; each of these Viterbi-detectors V00, V01,V02, V03, V04 has as output the bit-decisions for the top bit-row. Eachof these Viterbi-detectors V00, V01, V02, V03, V04 also uses the signalwaveform samples at the bit-row above the stripe as additional extra rowin the branch metrics; the weight of the signal waveform samples in thebottom row of the stripe is reduced below the maximum value (set equalto 1). In analogy, the Viterbi-detectors V00 a, V01 a, V02 a, V03 a arecascaded one after the other (also with mutual delay for back-trackingpurposes) starting from the bottom guard-band 80 towards the center ofthe broad spiral; each of these detectors V00 a, V01 a, V02 a, V03 a hasas output the bit-decisions for the bottom bit-row. Each of theseViterbi-detectors V00 a, V01 a, V02 a, V03 a also uses the signalwaveform samples at the bit-row below the stripe as additional extra rowin the branch metrics; the weight of the signal waveform samples in thetop row of the stripe is reduced below the maximum value (set equal to1). These two sets of cascaded Viterbi-detectors V00, V01, V02, V03, V00a, V01 a, V02 a, V03 a have a mutual mirror-type of relationship.Finally, the two cascades of detectors for the stripes are terminated inthe middle of the broad spiral with a last detector V04 a for the laststripe 44 f, which is the only detector for a stripe that has as outputits two bit-rows, and which has extra exterior bit-rows on both sides ofthe stripe (of which the signal waveforms are included in thecomputation of the branch metrics of that stripe); also the weights ofall signal waveforms at the branch-bits are set equal to the maximumvalue 1 (since the bit-rows at both sides of this stripe have beendetermined during execution of the two cascades of Viterbi-detectors inall previous stripes).

With the V-shaped stripe-wise bit-detector V00, V01, V02, V03, V00 a,V01 a, V02 a, V03 a, V04, V04 a, the propagation direction of“bit-reliability” is from the known bits of the guard band 46, 80towards the bit-row 44 f in the middle of the broad spiral, which arethus the largest distance from the guard bands: the “known” informationis propagated from both sides towards the middle, which is a betterapproach than propagating from top to bottom of the broad spiral.

In the particular case of a broad spiral with two guard bands 46, 80with bits that are known to the detector, the bit-reliability of the twoanchor bit-rows 46, 80 is 100%. To utilize both guard bands 46, 80 thelinear row of trailing detectors can be reshaped into a V shape as shownin FIG. 8. This not only utilizes the reliability of both guard bands46, 80 by propagating the reliability through the increased reliabilityof the side information that each detector provides to the next,trailing detector, it also reduces the total time required to performthe detection since the first detectors V00, V00 a, V01, V01 a, V02, V02a, V03, V03 a work in parallel providing the last detectors V04, V04 asooner with the required side information. As an alternative to the lasttwo detectors V04, V04 a a single detector that processes the middlethree bit rows 44 e, 44 f, 44 g at the same time, instead of just tworows, can be used. The overall reliability of the V shape is higher thanin the case of the regular linear row of detectors because the finaldetector or detectors V04, V04 a receive their side information throughless intermediate detectors V00, V00 a, V01, V01 a, V02, V02 a, V03, V03a.

The idea of this subsection can be generalized in the following way: thestripes can be cascaded as two sets forming a V-shaped configurationbetween any pair of two bit-rows in the 2D area that have asignificantly higher bit-reliability, so that they can serve as anchorpoints from which successive stripes can propagate in a two-sided waytowards each other in the middle area between the two rows with highbit-reliability. In the particular case of a broad spiral with two guardbands 46, 80 with bits that are known to the detector, thebit-reliability of the two anchor bit-rows is 100%. Another example isthe case of a 2D format with an extra bit-row in the middle of thespiral, that is encoded such that it has a higher bit-reliability thanthe other rows; then, two V-shaped progressions of detectors processingthe stripes can be devised, one operating between the center bit-row 44f and the upper guard band 46, the other operating between the samecenter bit-row 44 f and the lower guard band 80. For instance, thecenter bit-row 44 f may be channel encoded with a ID runlength limited(RLL) channel code that enables robust transmission over the channel:for instance, a d=1 RLL channel code removes some of the clusters, thosewith a “1” central bit and all six “0”'s as neighbour bits, and viceversa, in the overlap area of the signal patterns, hereby increasing therobustness of bit-detection on the one hand, but reducing the storagecapacity for that row on the other hand because of the constrainedchannel coding.

During back-tracking of a Viterbi-processor for a given stripe, it is anoption to output all bit-rows of the stripe so that a bit-array with themost recent bit-estimates are stored. The purpose of this measure is toachieve a more uniform architecture for the Viterbi-processors in thetop-half, bottom-half and central area of a V-shaped bit-detectionscheme.

Prior to any Viterbi bit-detection, it is advantageous to have somepreliminary bit-decisions albeit at a relatively poor bit-error rate(bER) performance. For instance, at one side of each stripe, bits thathave been determined from the previous stripe or are set to zero whenthe stripe is located directly next to the guard band; at the other sideof the stripe, bit-decisions are needed in order to be able to derivereference levels for the bits in the neighbouring bit stripe within thestripe: these bit-decisions can be derived from a previous iteration ofthe stripe-wise bit-detector, or from preliminary bit-decisions when thefirst iteration of the stripe-wise bit-detector is being executed. Thesepreliminary decisions can just be obtained by putting all bits to zero,which is not such a clever idea

A better approach is to apply threshold detection based on thresholdlevels, i.e. slicer levels, that depend on whether the row isneighbouring the guard band consisting of all zeroes or not. In the caseof a bit-row 44 a, 44 k neighbouring the guard band 46, 80, somecluster-levels are forbidden. Consequently, the threshold level isshifted upwards. It is computed as the level between the cluster-levelfor a central bit equal to 0 and three 1-bits as neighbour, and thecluster-level for a central bit equal to 1 and one 1-bit as neighbour.The expected bit-error rate of this simple threshold detection is then,for this case, equal to 2/32, which is about 6%. In the case of abit-row that is not neighbouring the guard-band, the threshold level iscomputed as the level between the cluster-level for a central bit equalto 0 and four 1-bits as neighbour, and the cluster-level for a centralbit equal to 1 and two 1-bits as neighbour. The expected bit-error rateof this simple threshold detection is then, for this case, equal to14/128, which is about 11%. Although these bERs are quite high, they areconsiderably better, especially at the bit-rows neighbouring the guardbands, than the 50% bER obtained through coin tossing. These preliminarybit-decisions obtained prior to the execution of the stripe-wisebit-detector can also be used as input for the adaptive control loops ofthe digital receiver (e.g. for timing recovery, gain- andoffset-control, adaptive equalization etc.) Note that the abovederivation of the proper slicer levels depends on the actual 2D storagedensity chosen and the resulting overlap of signal levels in the “SignalPatterns”.

1. A stripe wise iterative symbol detection method for detecting symbolvalues of a data block recorded along an N-dimensional channel tube, Nbeing at least 2, on a record carrier of a set of symbol rows, onedimensionally evolving along a first direction and being aligned witheach other along at least a second of N-1 other directions, said firstdirection together with said N-1 other direction constituting anN-dimensional lattice of symbol positions, wherein a stripe is a subsetof a row and at least one neighboring row, the iteration of said stripewise iterative symbol detection comprises: estimating the symbol valuesin a first stripe, using a search based algorithm, a side informationderived from a row adjacent to the first stripe, the side informationbeing used in the estimation of said symbol values, characterized inthat a weighing of a contribution of the side information is assignedbased on a reliability of the side information
 2. A stripe wiseiterative symbol detection method as claimed in claim 1, characterizedin that the contribution is a contribution to an objective function ofthe search based algorithm.
 3. A stripe wise iterative symbol detectionmethod as claimed in claim 2, characterized in that the search basedalgorithm comprises the use of contributions internal to the stripe andthat the use of the internal contributions comprises assigning anindividual weighing of the internal contributions
 4. A stripe wiseiterative symbol detection method as claimed in claim 1, characterizedin that the search based algorithm is a Viterbi algorithm, a sequentialdecoding algorithm such as a stack algorithm or a Fano algorithm, or asoft-decision output algorithm such as a (Max)(Log)MAP algorithm.
 5. Astripe wise iterative symbol detection method as claimed in claim 4,characterized in that the side information is an estimated channel inputsymbol
 6. A stripe wise iterative symbol detection method as claimed inclaim 4, characterized in that the side information is likelihoodinformation about a channel input symbol.
 7. A stripe wise iterativesymbol detection method as claimed in claim 5, characterized in that afurther side information, derived from the row adjacent to the firststripe, is being used in the estimation of said symbol values.
 8. Astripe wise iterative symbol detection method as claimed in claim 7,characterized in that the further side information comprises channeloutput values.
 9. A stripe wise iterative symbol detection method asclaimed in claim 8, characterized in that the channel output values arefiltered channel output values
 10. A stripe wise iterative symboldetection method as claimed in claim 1, characterized in that a weighingof the contribution of the side information is highest for sideinformation derived from a symbol detection with a highest reliability.11. A stripe wise iterative symbol detection method as claimed in claim11, characterized in that the symbol detection with the highestreliability is a symbol detection from a previous iteration.
 12. Astripe wise iterative symbol detection method as claimed in claim 10,characterized in that the weighing is based on a distance between aposition of a symbol value to be detected and a position of a sideinformation symbol position
 13. A stripe wise iterative symbol detectionmethod as claimed in claim 12, characterized in that the distance is adistance to a most reliable side information position
 14. A stripe wiseiterative symbol detection method as claimed in claim 10, characterizedin that the weighing of the contribution of the side information isdifferent for the second detector compared to the first detector
 15. Astripe wise iterative symbol detection method as claimed in claim 10,characterized in that the weighing of the contribution of the sideinformation is different for a second iteration compared to a firstiteration.
 16. A stripe wise iterative symbol detection method asclaimed in claim 15, characterized in that the weighing of thecontribution of the side information is higher for the second iterationcompared to the first iteration.
 17. A stripe wise iterative symboldetection method as claimed in claim 10, characterized in that the sideinformation is obtained from a row comprising data which is highlyprotected using redundant coding.
 18. A stripe wise iterative symboldetection method as claimed in claim 10, characterized in that the sideinformation is obtained from a row comprising predefined data.
 19. Astripe wise iterative symbol detection method as claimed in claim 17,characterized in that the row comprising data which is highly protectedusing redundant coding is a guard band
 20. A stripe wise iterativesymbol detection method as claimed in claim 17, characterized in thatthe row comprising data which is highly protected using redundant codingis located centrally between the rows forming the set of symbol rows.21. A stripe wise iterative symbol detection method as claimed in claim19, characterized in that the N-Dimensional channel tube is delimited byone or more guard bands.
 22. A stripe wise iterative symbol detectionmethod as claimed in claim 19, characterized in that side information isderived from each guard band of the one or more guard bands
 23. A symboldetector comprising a first detector comprising estimation means forestimating symbol values in a first stripe, receiving means forreceiving side information derived from at least one row adjacent to thefirst stripe, coupled to the estimation means for providing said sideinformation to the estimation means for use in the estimation of saidsymbol values and output means for providing further side information,and a second detector comprising further estimation means for estimatingsymbol values in a second stripe, further receiving means for receivingside information derived from the output of the first detector coupledto the further estimation means for providing said side information tothe further estimation means for use in the estimation of said symbolvalues from the second stripe.
 24. A playback device comprising a symboldetector as claimed in claim 23
 25. A computer program using one of themethod of claim 1.